
Likes, Comments, Views
Author(s) -
Jylisa Doney,
Olivia Wikle,
Jessica Martínez
Publication year - 2020
Publication title -
information technology and libraries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.502
H-Index - 34
eISSN - 2163-5226
pISSN - 0730-9295
DOI - 10.6017/ital.v39i3.12211
Subject(s) - crowdsourcing , social media , world wide web , content analysis , academic library , content (measure theory) , computer science , sociology , library science , mathematical analysis , social science , mathematics
This article presents a content analysis of academic library Instagram accounts at eleven land-grant universities. Previous research has examined personal, corporate, and university use of Instagram, but fewer studies have used this methodology to examine how academic libraries share content on this platform and the engagement generated by different categories of posts. Findings indicate that showcasing posts (highlighting library or campus resources) accounted for more than 50 percent of posts shared, while a much smaller percentage of posts reflected humanizing content (emphasizing warmth or humor) or crowdsourcing content (encouraging user feedback). Crowdsourcing posts generated the most likes on average, followed closely by orienting posts (situating the library within the campus community), while a larger proportion of crowdsourcing posts, compared to other post categories, included comments. The results of this study indicate that libraries should seek to create Instagram posts that include various types of content while also ensuring that the content shared reflects their unique campus contexts. By sharing a framework for analyzing library Instagram content, this article will provide libraries with the tools they need to more effectively identify the types of content their users respond to and enjoy as well as make their social media marketing on Instagram more impactful.